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Quantification of Patient-Reported Pain Locations: Development of an Automated Measurement Method.
Abudawood, Khulud; Yoon, Saunjoo L; Garg, Rishabh; Yao, Yingwei; Molokie, Robert E; Wilkie, Diana J.
Affiliation
  • Abudawood K; Author Affiliations: College of Nursing, King Saud bin Abdulaziz University for Health Sciences (Dr Abudawood), Jeddah, Saudi Arabia; Department of Biobehavioral Nursing Science, College of Nursing (Drs Yoo, Yao, and Wilkie), and Herbert Wertheim College of Engineering (Mr Garg), University of Florida, Gainesville; Department of Biobehavioral Health Science, College of Nursing (Dr Wilkie), and Department of Medicine, College of Medicine (Dr Molokie), University of Illinois at Chicago; and Jesse
Comput Inform Nurs ; 41(5): 346-355, 2023 May 01.
Article in En | MEDLINE | ID: mdl-36067491
ABSTRACT
Patient-reported pain locations are critical for comprehensive pain assessment. Our study aim was to introduce an automated process for measuring the location and distribution of pain collected during a routine outpatient clinic visit. In a cross-sectional study, 116 adults with sickle cell disease-associated pain completed PAIN Report It Ⓡ . This computer-based instrument includes a two-dimensional, digital body outline on which patients mark their pain location. Using the ImageJ software, we calculated the percentage of the body surface area marked as painful and summarized data with descriptive statistics and a pain frequency map. The painful body areas most frequently marked were the left leg-front (73%), right leg-front (72%), upper back (72%), and lower back (70%). The frequency of pain marks in each of the 48 body segments ranged from 3 to 79 (mean, 33.2 ± 21.9). The mean percentage of painful body surface area per segment was 10.8% ± 7.5% (ranging from 1.3% to 33.1%). Patient-reported pain locations can be easily analyzed from digital drawings using an algorithm created via the free ImageJ software. This method may enhance comprehensive pain assessment, facilitating research and personalized care over time for patients with various pain conditions.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Algorithms / Software Type of study: Observational_studies / Risk_factors_studies Limits: Adult / Humans Language: En Journal: Comput Inform Nurs Journal subject: ENFERMAGEM / INFORMATICA MEDICA Year: 2023 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Algorithms / Software Type of study: Observational_studies / Risk_factors_studies Limits: Adult / Humans Language: En Journal: Comput Inform Nurs Journal subject: ENFERMAGEM / INFORMATICA MEDICA Year: 2023 Document type: Article
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